Computing unit: one fit-PC2 motherboard based on Intel Atom Z530 from
CompuLab.

Labor hours: 380.

Distribution: Ubuntu Linux 9.08.

Software used: GEdit, OpenCV and C++.

Scientific field: neural networks and adaptation methods.

AB: Can you estimate how much time
(in hours) it took to
construct the hexapod (put together the mechanical and electrical parts) and
write the software itself?

MB: Ha ha. It is an enormous amount for
sure. I worked on it for hours a day,
weeks at a time. The original Q-Learning robot probably took 200 hours. Then I
gave it a makeover, which took maybe 100 hours, and then the other projects took maybe 80
each.

AB: You said previously that the operating system beneath the cover is
Ubuntu. What IDE did you use to write the robot's middleware—Qt,
WxWidgets,
ncurses or something else?

MB: I actually use only GEdit and purely in C++ using OpenCV libraries. The
simulations I built were done purely using OpenCV, drawing individual lines at
a time. I feel like I re-invent the wheel when I do this, but I sure learn a
lot!

First experiment is done in simulated environment.

AB: Do you release schematics and
auxiliary software of a robot under the GPL or
under another license?

MB: I have been looking to release my kinematics code under a license, but I
know nothing in this area. Maybe LJ readers could point me in
the right direction?

AB: You're a senior student at the
University of Arizona, and this project is to
some degree your graduation work. Do you plan to continue its future
development?

MB: I look forward to implementing more functionality into the hexapod as a
graduate student at the University of Arizona. Currently, I am working on a
miniature version. I do want to explore the link between vision and
legged locomotion through the use of biologically inspired neural networks
further.

AB: Where, in your opinion, can this
“spider” be used and be useful for
people?

MB: The hexapod could make a great
search-and-rescue-style robot. In a
natural disaster like an earthquake, it would be desirable to have a large
number of robots searching autonomously for survivors in a building turned to
rubble. The environment is treacherous though and could cause damage to the
robot. Once damage is inflicted upon the hexapod, a purely inverse
kinematic-based hexapod would be rendered useless. If, however, it could
re-learn, the
hexapod still could operate given its new configuration. Like I mentioned
previously though, it is more of a tool to explore machine learning techniques
and out of the research, hopefully discover faster algorithms. Hopefully, better
algorithms can be used for consumer-based robotics to increase the standard.

AB: Do you plan to use the hexapod or your next prototype CrustCrawler in
autonomous walking research?

MB: Sure. The learning mechanisms I've implemented are more scientific, and I
certainly encourage everyone to explore science with robotics platforms, but
it is not necessarily the goal for the CrustCrawler platform. I see that as a
means of making it easy for anyone to get started in the field of hexapod
robotics. If the different geometry is more conducive to what I want the
hexapod to do, then I will, of course, use it. The hexapods are simply tools in
my mind for research. I certainly want my hexapods to be able to roam around
on their own and accomplish some task even if it is mundane. The nice thing
about the CrustCrawler hexapod and my personal hexapod is that they can be
easily interchanged, as they use motors that communicate using identical
protocols. All I have to do is change a few geometric calibration settings and
it will run just fine.

Photos courtesy Matt Bunting, Intel Corp.

Anton Borisov has broad spheres of interests, ranging from clusters and
embedded devices to artificial intelligence and programmatic puzzles. One
thing that unites them all is Linux, his most favorite operating system.